3,896 research outputs found
Furniture models learned from the WWW: using web catalogs to locate and categorize unknown furniture pieces in 3D laser scans
In this article, we investigate how autonomous robots can exploit the high quality information already available from the WWW concerning 3-D models of office furniture. Apart from the hobbyist effort in Google 3-D Warehouse, many companies providing office furnishings already have the models for considerable portions of the objects found in our workplaces and homes. In particular, we present an approach that allows a robot to learn generic models of typical office furniture using examples found in the Web. These generic models are then used by the robot to locate and categorize unknown furniture in real indoor environments
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review
Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519
Task-Oriented and Semantics-Aware 6G Networks
Upon the arrival of emerging devices, including Extended Reality (XR) and
Unmanned Aerial Vehicles (UAVs), the traditional bit-oriented communication
framework is approaching Shannon's physical capacity limit and fails to
guarantee the massive amount of transmission within latency requirements. By
jointly exploiting the context of data and its importance to the task, an
emerging communication paradigm shift to semantic level and effectiveness level
is envisioned to be a key revolution in Sixth Generation (6G) networks.
However, an explicit and systematic communication framework incorporating both
semantic level and effectiveness level has not been proposed yet. In this
article, we propose a generic task-oriented and semantics-aware (TOSA)
communication framework for various tasks with diverse data types, which
incorporates both semantic level information and effectiveness-aware
performance metrics. We first analyze the unique characteristics of all data
types, and summarise the semantic information, along with corresponding
extraction methods. We then propose a detailed TOSA communication framework for
different time-critical and non-critical tasks. In the TOSA framework, we
present the TOSA information, extraction methods, recovery methods, and
effectiveness-aware performance metrics. Last but not least, we present a TOSA
framework tailored for Unmanned Aerial Vehicle (UAV) control task to validate
the effectiveness of the proposed TOSA communication framework
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